From　the　perspective　of　the　geographical　distribution,　considering　production　fare,　supply　chain　information　and　quality　rating　of　the　manufacturing　resource　(MR),　a　manufacturing　resource　allocation　(MRA)　model　considering　the　geographical　distribution　in　cloud　manufacturing　(CM)　environment　is　built.　The　model　includes　two　stages,　preliminary　selection　stage　and　optimal　selection　stage.　The　membership　function　is　used　to　select　MRs　from　cloud　resource　pool　(CRP)　in　the　first　stage,　and　then　the　candidate　resource　pool　is　built.　In　the　optimal　selection　stage,　a　multi-objective　optimization　algorithm,　particle　swarm　optimization　(PSO)　based　on　the　method　of　relative　entropy　of　fuzzy　sets　(REFS_PSO),　is　used　to　select　optimal　MRs　from　the　candidate　resource　pool,　and　an　optimal　manufacturing　resource　supply　chain　is　obtained　at　last.　To　verify　the　performance　of　REFS_PSO,　NSGA-II　and　PSO　based　on　random　weighting　(RW_PSO)　are　selected　as　the　comparison　algorithms.　They　all　are　used　to　select　optimal　MRs　at　the　second　stage.　The　experimental　results　show　solution　obtained　by　REFS_PSO　is　the　best.　The　model　and　the　method　proposed　are　appropriate　for　MRA　in　CM.　©　2019,　The　Editorial　Department　of　Journal　of　Harbin　Institute　of　Technology.　All　right　reserved.